A CT scanner generally includes an x-ray tube mounted on a rotatable gantry opposite a detector array located across an examination region. The rotatable gantry, and hence the x-ray tube, rotates around the examination region, and the x-ray tube emits radiation that traverses the examination region and a portion of a subject therein. The detector array detects the radiation and generates projection data indicative thereof. A reconstructor reconstructs the projection data and generates 3D volumetric image data representative of the scanned portion of the subject.
Suitable reconstruction algorithms include iterative reconstruction algorithms such as a maximum likelihood iterative reconstruction (MLIR) algorithm, etc., and non-iterative reconstruction algorithms such as filtered back projection (FBP), etc. The 3D volumetric image data includes voxels that are represented in terms of gray scale intensity values corresponding to relative radiodensity for CT (and other material qualities for MR, PET, SPECT, US, respectively). The gray scale values (intensities) reflect the attenuation characteristics of the scanned subject and/or object, and generally show structure such as anatomical structures within the scanned patient or object.
The 3D volumetric image data can be processed to create a 2D projection of the 3D volumetric image data. One such approach is direct volume rendering (DVR). With DVR, each voxel value of the 3D volumetric image data is mapped to a color value, an opacity value, and a gradient value. Once mapped, these properties are then projected from 3D volume space into 2D image space, such as the pixels of a display monitor, by combining them along view rays into rendering pixels. In another application, the 3D volumetric image data from two different image data sets can be processed to register (or spatially align) the data sets. Both applications, volume rendering and registration, are dependent on a noise estimate for the image volume(s). Unfortunately, global noise parameters may not accurately reflect the local voxel noise level, which may degrade the resulting image quality for volume rendering, and the resulting spatial accuracy for registration.